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Sushidata
APIs for swarms of agents that compound data and save tokens
Great sushi depends on the quality of its ingredients. AI is the same. The intelligence of an agent depends on quality context it can access. Today, agents fetch the same raw ingredients, rescraping data and resummarizing sources while wasting tokens. Sushidata is a context lake and API for swarms of agents. Agents gather data from competitive intel, GTM research, VoC, and communities, storing them in a shared context lake that swarms can reuse and compound instead of starting from scratch.
A HUGE thank you to everyone who helped us get here.
We built Sushidata because teams still spend too much time stitching together competitive intelligence, GTM research, and voice-of-customer insights by hand. Even with tools like ChatGPT or Claude, the work/context often remains fragmented and manual. The same data gets collected, summarized, and analyzed again and again.
Sushidata changes that by creating a shared context layer for swarms of agents. It connects to the data sources you already use and turns them into a compounding knowledge base that agents can reuse instead
of rebuilding context from scratch. This saves tokens and improves accuracy.
Just ask Sushi or use our Swarm API and it will deploy agents that gather the data for you. Sushidata orchestrates the agents and determines how the results should be structured and represented so you get deeper, more connected intelligence. Bring the data anywhere, to Claude, Codex, or whichever tool people will use in the future. It's your research, so why not carry it with you anywhere you go?
Setting it up takes literally 2 minutes.
Everything gets saved, and the context compounds over time for anyone running the same skill file (which you can download when you make your first API)
Would love you to try it! Show us your support, feedback, and thoughts in the comments!
About Sushidata on Product Hunt
“APIs for swarms of agents that compound data and save tokens”
Sushidata was submitted on Product Hunt and earned 18 upvotes and 1 comments, placing #85 on the daily leaderboard. Great sushi depends on the quality of its ingredients. AI is the same. The intelligence of an agent depends on quality context it can access. Today, agents fetch the same raw ingredients, rescraping data and resummarizing sources while wasting tokens. Sushidata is a context lake and API for swarms of agents. Agents gather data from competitive intel, GTM research, VoC, and communities, storing them in a shared context lake that swarms can reuse and compound instead of starting from scratch.
On the analytics side, Sushidata competes within API, Marketing and Developer Tools — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Sushidata performed against the three products that launched closest to it on the same day.
Who hunted Sushidata?
Sushidata was hunted by George Portillo. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
George Portillo
A HUGE thank you to everyone who helped us get here.
We built Sushidata because teams still spend too much time stitching together competitive intelligence, GTM research, and voice-of-customer insights by hand. Even with tools like ChatGPT or Claude, the work/context often remains fragmented and manual. The same data gets collected, summarized, and analyzed again and again.
Sushidata changes that by creating a shared context layer for swarms of agents. It connects to the data sources you already use and turns them into a compounding knowledge base that agents can reuse instead
of rebuilding context from scratch. This saves tokens and improves accuracy.
Just ask Sushi or use our Swarm API and it will deploy agents that gather the data for you. Sushidata orchestrates the agents and determines how the results should be structured and represented so you get deeper, more connected intelligence. Bring the data anywhere, to Claude, Codex, or whichever tool people will use in the future. It's your research, so why not carry it with you anywhere you go?
Setting it up takes literally 2 minutes.
Everything gets saved, and the context compounds over time for anyone running the same skill file (which you can download when you make your first API)
Would love you to try it! Show us your support, feedback, and thoughts in the comments!